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Discuss the optimization techniques for batch processing in PySpark. How can you ensure that your batch processing jobs are efficient and scalable?
A
Use dynamic partitioning to automatically adjust the number of partitions based on the data size, which can help in optimizing resource usage.
B
Optimize batch processing by reducing the number of transformations and using more efficient data formats like Parquet.
C
Batch processing should always be run with the maximum number of partitions to ensure the highest level of parallelism and efficiency.
D
Batch processing optimization is not necessary as PySpark automatically handles all optimizations.
